Fast-moving target tracking based on mean shift and frame-difference methods

The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrating the mean shift algorithm and frame-difference methods. The rough position of the moving tar- get is first located by the direct frame-difference algorithm and three-frame-difference algorithm for the immobile camera scenes and mobile camera scenes, respectively. Then, the mean shift algorithm is used to achieve precise tracking of the target. Several tracking experiments show that the proposed method can effectively track first moving targets and overcome the tracking error accumulation problem.

A Novel Rolling Bearing Vibration Impulsive Signals Detection Approach Based on Dictionary Learning

The localized faults of rolling bearings can be diagnosed by its vibration impulsive signals.However,it is always a challenge to extract the impulsive feature under background noise and non-stationary conditions.This paper investigates impulsive signals detection of a single-point defect rolling bearing and presents a novel data-driven detection approach based on dictionary learning.To overcome the effects harmonic and noise components,we propose an autoregressive-minimum entropy deconvolution model to separate harmonic and deconvolve the effect of the transmission path.To address the shortcomings of conventional sparse representation under the changeable operation environment,we propose an approach that combines K-clustering with singular value decomposition(K-SVD)and split-Bregman to extract impulsive components precisely.Via experiments on synthetic signals and real run-to-failure signals,the excellent performance for different impulsive signals detection verifies the effectiveness and robustness of the proposed approach.Meanwhile,a comparison with the state-of-the-art methods is illustrated,which shows that the proposed approach can provide more accurate detected impulsive signals.

A Novel Product Remaining Useful Life Prediction Approach Considering Fault Effects

In this paper,a novel remaining useful life prediction approach considering fault effects is proposed.The Wiener process is used to construct the degradation process of single performance characteristic with the fault effects.The first passage time based remaining useful life distribution is calculated by assuming fault occurrence moment is a random variable and follows a certain distribution.Expectation maximization algorithm is employed to estimate model parameters,where the fault occurrence moment is considered as a missing data.Finally,a Copula function is used to describe the dependence between the multiple performance characteristics and derive joint remaining useful life(RUL)distribution of product with the fault effects.The effectiveness of the proposed approach is verified by the experiments of turbofan engines.

Termination of Recurrent Atrial Fibrillation by Superior Vena Cava Isolation: A Case Report

Background:Paroxysmal atrial fibrillation can be triggered by non-pulmonary vein foci,such as the superior vena cava.Here,we report the case of a patient with a 6-year history of paroxysmal atrial fibrillation who received cryoballoon ablation in 2012 but relapsed in 2014.He then received cardiac radiofrequency ablation,which successfully isolated the left pulmonary vein and superior vena cava,but the arrhythmia recently relapsed again.The tachycardia was finally successfully terminated by ablation on the free wall without recurrence during a 2-year following up.Conclusion:Superior vena cava isolation may not require ablation isolation with a full circle way and can be accomplished by ablating several connection points between the superior vena cava and the right atrium.

Mechanisms of Myocardial Stunning in Stress-Induced Cardiomyopathy

Stress-induced cardiomyopathy,in contrast to acute myocardial infarction,is a type of acute heart failure characterized by reversible left ventricular dysfunction.Cardiac imaging primarily reveals left ventricle myocardial stunning,81.7%of which is apical type.Emotional or psychological stress usually precedes the onset of stress-induced cardiomyopathy,which is increasingly being recognized as a unique neurogenic myocardial stunning disease.To distinguish between acute myocardial infarction and acute viral or auto-immune myocarditis,this review summarizes specific mechanisms of myocardial stunning in stress-induced cardiomyopathy,such as calcium disorders,metabolic alterations,anatomical and histological variations in different parts of the left ventricle,and microvascular dysfunction.

Role of Epicardial Adipose Tissue in Triggering and Maintaining Atrial Fibrillation

Atrial fibrillation is the most common arrhythmia leading to cardiogenic stroke.Without membranous sructure between epicardial adipose tissue and atrial myocardium,epicardial adipose tissue directly covers the surface of the atrial myocardium.The formation of an epicardial adipose tissue inflammatory microenvironment,fibrosis,infiltration by epicardial adipose tissue,autonomic dysfunction and oxidative stress are important mechanisms that trigger and maintain atrial fibrillation.Those mechanisms are reviewed herein.

The Role of Sleep Deprivation in Arrhythmias

Sleep is essential to the normal psychological and physiological activities of the human body.Increasing evidence indicates that sleep deprivation is associated with the occurrence,development,and poor treatment effects of various arrhythmias.Sleep deprivation affects not only the peripheral nervous system but also the central nervous system,which regulates the occurrence of arrhythmias.In addition,sleep deprivation is associated with apoptotic pathways,mitochondrial energy metabolism disorders,and immune system dysfunction.Although studies increasingly suggest that pathological sleep patterns are associated with various atrial and ventricular arrhythmias,further research is needed to identify specific mechanisms and recommend therapeutic interventions.This review summarizes the findings of sleep deprivation in animal experiments and clinical studies,current challenges,and future research directions in the field of arrhythmias.

A survey on distributed compressed sensing： theory and applications

The compressed sensing （CS） theory makes sample rate relate to signal structure and content. CS samples and compresses the signal with far below Nyquist sampling frequency simultaneously. However, CS only considers the intra-signal correlations, without taking the correlations of the multi-signals into account. Distributed compressed sensing （DCS） is an extension of CS that takes advantage of both the inter- and intra-signal correlations, which is wildly used as a powerful method for the multi-signals sensing and compression in many fields. In this paper, the characteristics and related works of DCS are reviewed. The framework of DCS is introduced. As DCS＇s main portions, sparse representation, measurement matrix selection, and joint reconstruction are classified and summarized. The applications of DCS are also categorized and discussed. Finally, the conclusion remarks and the further research works are provided.